Information Technology Reference
In-Depth Information
Chapter 5
Grand Challenges in Computational
Movement Analysis
This final chapter addresses the prospect of Computational Movement
Analysis (CMA) as a relatively young research field. The first decade of CMA was
shaped by significant technological developments resulting in much increased avail-
ability of fine-grained movement data, an innocent and somewhat naïve enthusiasm
over moving points resulting in a wide but fragmented variety of methods for move-
ment analysis, and finally due to this lack of a unifying theory of CMA only moderate
success in overcoming GIS' and GIScience' legacy of static cartography. The final
chapter concludes this topic by proposing a set of grand challenges of CMA. The
grand challenges arise from observations about current trends in CMA and my per-
sonal view on where this young and important research field will develop in the years
to come.
This topic argues that CMA is an emerging research field with ample momentum
witnessing rapid development in many related research fields and application areas.
Preparing the discussion of the
grand challenges
of the field to follow in the next
section, it is here worth back-pedaling for a moment, and trying to capture the current
state of a field seemingly moving forwards with giant steps. The following list gives
an overviewof trends and developments that arguably have andwill have implications
for the further development of the young research field.
Movement data becomes more available. Scientists from a wide range of applica-
tion fields are more willing to share their data.
Following miniaturization and reduced costs, movement data sets cover more and
more individuals at ever finer granularities.
The movement data sets typically used for CMA change their character: Large
repositories capturing trajectory data of massive sets of individuals as a “byprod-
uct” (as for example form GSM networks) outplay purposefully collected move-
ment data sets tracking small numbers of individuals (most movement ecology
studies tracking samples sizes of a couple of dozens).
Data repositories simplifying data exchange amongst scientists are established
(for example,
http://www.movebank.org
)
and gain momentum.
